Automatic Inter-subject Registration of Whole Body Images

Abstract

3D inter-subject registration of image volumes is important for tasks such as atlas-based segmentation, deriving population averages, or voxel and tensor-based morphometry. A number of methods have been proposed to tackle this problem but few of them have focused on the problem of registering whole body image volumes acquired either from humans or small animals. These image volumes typically contain a large number of articulated structures, which makes registration more difficult than the registration of head images, to which the vast majority of registration algorithms have been applied. This paper pre-sents a new method for the automatic registration of whole body CT volumes, which consists of two steps. Skeletons and external surfaces are first brought into approximate correspondence with a robust point-based method. Trans-formations so obtained are refined with an intensity-based algorithm that includes spatial adaptation of the transformation’s stiffness. The approach has been applied to whole body CT images of mice and to CT images of the human upper torso. We demonstrate that the approach we propose can successfully register image volumes even when these volumes are very different in size and shape or if they have been acquired with the subjects in different positions.